FinBERT is a pre-trained NLP model for financial sentiment analysis, built by fine-tuning the BERT language model on a large financial corpus. The model provides softmax outputs for three labels: positive, negative, or neutral.
FinBERT is a pre-trained NLP model for financial sentiment analysis, built by fine-tuning the BERT language model on a large financial corpus. The model provides softmax outputs for three labels: positive, negative, or neutral.
text to classify
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POSITIVE (1.00)
NEGATIVE (0.00)
FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. Financial PhraseBank by Malo et al. (2014) is used for fine-tuning. For more details, please see the paper FinBERT: Financial Sentiment Analysis with Pre-trained Language Models and our related blog post on Medium.
The model will give softmax outputs for three labels: positive, negative or neutral.
About Prosus
Prosus is a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities. For more information, please visit www.prosus.com.
Contact information
Please contact Dogu Araci dogu.araci[at]prosus[dot]com and Zulkuf Genc zulkuf.genc[at]prosus[dot]com about any FinBERT related issues and questions.